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Sablefish ( Anoplopoma fimbria ) produce high frequency rasp sounds with frequency modulation

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Sablefish sounds, named rasps, were recorded at two captive facilities in British Columbia and Washington State. Rasps consisted of highly variable broadband trains of 2 to 336 ticks that lasted between 74 and 10 500 ms. The 260 rasps that were measured contained frequencies between 344 and 34 000 Hz with an average peak frequency of 3409 Hz. The frequency structure of ticks within rasps was highly variable and included both positive and negative trends. This finding makes sablefish one of the few deep-sea fish for which sounds have been validated and described. The documentation of sablefish sounds will enable the use of passive acoustic monitoring methods in fisheries and ecological studies of this commercially important deep-sea fish.
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Sablefish (Anoplopoma fimbria) produce high frequency rasp
sounds with frequency modulation
Amalis Riera,
Rodney A. Rountree, Lucas Agagnier, and Francis Juanes
Department of Biology, University of Victoria, 3800 Finnerty Road, Victoria, BC V8P 5C2, Canada
Sablefish sounds, named rasps, were recorded at two captive facilities in British Columbia and Washington State.
Rasps consisted of highly variable broadband trains of 2 to 336 ticks that lasted between 74 and 10 500ms. The 260
rasps that were measured contained frequencies between 344 and 34 000 Hz with an average peak frequency of
3409 Hz. The frequency structure of ticks within rasps was highly variable and included both positive and negative
trends. This finding makes sablefish one of the few deep-sea fish for which sounds have been validated and
described. The documentation of sablefish sounds will enable the use of passive acoustic monitoring methods in fish-
eries and ecological studies of this commercially important deep-sea fish. V
C2020 Acoustical Society of America.
(Received 5 December 2019; revised 17 March 2020; accepted 24 March 2020; published online 16 April 2020)
[Editor: Arthur N. Popper] Pages: 2295–2301
Fish sounds have been studied since at least the late
1800 s (Dufoss
e, 1874) and since then there have been numer-
ous accounts of the variability that exists in fish sound pro-
duction (Fish, 1948;Fish et al., 1952;Moulton, 1963;
Schneider, 1966;Tavolga, 1971;Hawkins, 1993;Kaatz,
2002;Ladich, 2004;Fine and Parmentier, 2015;Zeyl et al.,
2016). The ability to recognize fish sounds is becoming
increasingly useful for passive acoustic monitoring (PAM)
studies on population and ecosystem health (Rountree et al.,
2006;Slabbekoorn et al.,2010;Riera et al., 2016;Archer
et al., 2018;Lindseth and Lobel, 2018). In order to use PAM,
examples of sounds from each species of fish need to be vali-
dated and available for comparison to the sounds recorded
through PAM (Rountree et al.,2002). There are currently
34 300 known fish species (Froese and Pauly, 2019)and
sound production has been reported for fewer than 1000 spe-
cies (Lobel et al.,2010), although an updated number remains
to be confirmed. This number is growing as new fish sounds
are being described (Wilson et al., 2004;Riera et al., 2018;
Rountree et al.,2018). Despite these efforts, the capacity for
sound production remains to be investigated for the majority
of fish species (Rountree et al.,2002,2019).
There is increasing interest in understanding the dynam-
ics and health of deep-sea ecosystems such as sponge reefs
(Archer et al., 2018), seamounts (Department of Fisheries
and Oceans Canada, 2011), and banks, as these systems are
fragile and vulnerable to overfishing (Koslow et al., 2000).
The soundscape of the deep sea is poorly known and the use
of PAM methods to study these ecosystems is becoming
more common (Rountree et al., 2012;Wall et al., 2014).
The deep-sea sablefish (Anoplopoma fimbria, order
Scorpaeniformes, family Anoplopomatidae), also known as
black cod, is an economically important ground fish native
to the North Pacific Ocean ranging from Baja California to
the Bering Sea and throughout the Aleutian Islands into
waters off the Kamchatka Peninsula, Russia, and northern
Japan (Wilkins and Saunders, 1997;Jacobson et al., 2001).
Adult sablefish inhabit the upper continental slope and deep
continental shelf at depths of 200–1280 m (Wilkins and
Saunders, 1997;Jacobson et al., 2001). Sablefish support
valuable commercial and recreational fisheries in Alaska
(Warpinski et al., 2016), Japan, Russia, and along the U.S.
West Coast (Koslow et al., 2000). In addition, thanks to its
high growth rate and market value, sablefish aquaculture is
developing in several countries, including the U.S. and
Canada (Sumaila et al., 2007;Sanchez-Serrano et al., 2014;
National Marine Fisheries Service, 2017). The sablefish was
first suggested to produce sounds in an unpublished study of
captive fish by Meldrim (1965) and later based on deep-sea
recordings associated with sablefish presence at deep-sea
observatories (Sirovic et al., 2012), but these observations
have not been substantiated. Confirmation of sablefish sound
production, together with a validated description of sablefish
sound characteristics, would provide researchers with a new
tool to monitor the species using passive acoustics.
The goal of this study was to determine if sablefish pro-
duce sounds, and if so, to provide validated sound descrip-
tions to enable future PAM studies of the species. Captive
sablefish were observed and recorded both in an open-water
aquaculture facility and in a sablefish research station.
A. Data collection
Acoustic recordings were obtained at two facilities:
Golden Eagle Sablefish Farm (GESF) (BC, Canada), where
This paper is part of a Special Issue on The Effects of Noise on Aquatic
Electronic mail:
J. Acoust. Soc. Am. 147 (4), April 2020 V
C2020 Acoustical Society of America 22950001-4966/2020/147(4)/2295/7/$30.00
a few hundred sablefish were held in 30 m
net pens, and the
NOAA Northwest Fisheries Science Center at Manchester
Research Station (NWFSC-MRS) (WA, USA), where 20–30
sablefish were held in 3.66 m diameter tanks. There were
only mature adult sablefish at GESF [size range: 46–85 cm
total length (TL)]. At the NWFSC-MRS adult sablefish (size
range: 35–75 cm TL) were monitored from seven tanks, and
juveniles (size range: 3–5 cm TL) from a single tank. The
adult sablefish at NWFSC-MRS were distributed in four
tanks with mixed sexes, one tank with only males, and two
tanks with unknown sexes.
At both facilities, sablefish were monitored for sound
production in real time. Recordings were made at 96 kHz
(24 bit), to a Zoom-H1 recorder (Zoom North America,
Hauppauge, NY) with an uncalibrated SQ26-01 hydrophone
(sensitivity ¼193.5 dB re: 1 V/lPa, Cetacean Research
Technology, Seattle, WA). At the NWFSC-MRS, water
pumps were turned off in order to reduce noise.
A Song Meter SM4 recorder (Wildlife Acoustics,
Maynard, MA) with an HTI hydrophone (sensitivity
¼165 dB re: 1 V/lPa, High Tech Inc., Long Beach, MS)
was also deployed in a tank containing juvenile sablefish at
NWFSC-MRS to collect data on a continuous duty cycle at
96 kHz (16 bit) for up to 4 days. No alterations were made to
the regular schedules of pumps and filters for SM4 recordings.
B. Data post-processing
Acoustic measurements of selected parameters of all
sablefish sounds were made in Raven Pro 1.5 acoustic soft-
ware (Center for Conservation Bioacoustics, 2014) follow-
ing Charif et al. (2010). Recordings were visually inspected
in their entirety to identify sablefish sounds. Spectrograms
were displayed 15 s at a time with frequencies between 0
and 11 kHz [2825 fast Fourier transform (FFT), Hann win-
dow, 85% overlap]. Selection boxes were drawn around
each sound to measure the sound duration, the lowest peak,
and highest frequency, the 5th and 95th percentile frequen-
cies (F. 5% and F. 95%, respectively), and bandwidth 90%
(BW 90%) (Charif et al., 2010). Raven Pro automatically
computed these values based on the selection boundaries. F.
5% is the frequency that divides the selection into two fre-
quency intervals containing 5% of the energy at the bottom
and 95% of the energy at the top, while F. 95% is the fre-
quency separating 95% of the energy at the bottom and 5%
at the top. BW 90% is the difference between F. 5% and F.
95% frequencies. The peak frequency is the frequency at
which maximum power occurs within the signal. For each
variable, the measurements reported include minimum,
maximum, and mean 6SE (standard error).
Sablefish sounds are comprised of a number of broad-
band ticks that are separated from each other by variable
durations. To differentiate between one sound and the next,
an arbitrary cutoff of 1 s was used.
A subset of 72 sablefish sounds from the NWFSC-MRS
was used to count the number of ticks per sound and mea-
sure tick-specific duration and frequency parameters (724
FFT, Hann window, 85% overlap). The duration between
ticks, or period, was calculated as the time between the
beginning of one tick and the beginning of the next tick
(Fig. 1). The inter-tick interval was calculated as the time
between the end of one tick and the beginning of the next
tick. The tick repetition rate was calculated by dividing the
number of ticks in a given sound by the duration of that
sound. Within-sound variation in tick frequency structure
(F. 5%, peak, F. 95%, and BW 90%) was tested for correla-
tion with elapsed time for 57 unique sounds having 8 or
more ticks. Spearman Rank correlation on log transformed
frequencies was performed due to non-linear data trends
using SAS/STAT software (SAS Institute Inc., 2012).
Mm. 1. Audio clip of short sablefish rasp (with fewer than
eight ticks) corresponding to the spectrogram displayed
in Fig. 1. This is a file of type “WAV” (561 KB).
Sounds attributed to adult sablefish were produced by
highly agitated fish that displayed aggressive behavior
(charging and nipping the hydrophone) during net pen trans-
fer at GESF. Similar sounds were recorded from captive
specimens at the NWFSC-MRS but were not associated
with any specific behavior.
Sounds were recorded at GESF between 2:00 pm and
6:00 pm. Sounds were recorded at the NWFSC-MRS in 5 C
water between 7:00 am and 4:30 pm. At NWFSC-MRS, two
or more rasps were heard in each of the four tanks that con-
tained mixed genders, and the tank that had only males. No
rasps were positively identified in the recordings from the
two tanks with unknown genders nor in the tank that con-
tained juveniles.
The duration of sablefish sounds ranged between 74 and
10 493 ms (average of 1342 696 SE; Table I) and they
FIG. 1. Waveform (top) and spectrogram (bottom) of a short rasp (with
fewer than eight ticks) produced by sablefish (Anoplopoma fimbria) at the
Northwest Fisheries Science Center in Manchester (1800 FFT Hann win-
dow with 85% overlap). The temporal measurements are illustrated: rasp
duration (a), tick duration (b), and period (c). A clip of the sound is avail-
able as a multimedia file (Mm. 1).
2296 J. Acoust. Soc. Am. 147 (4), April 2020 Riera et al.
consisted of highly variable trains of 3 to 336 ticks (average
30 65, Table II).
Due to the similarity of these sounds with cetacean
rasps (Marrero P
erez et al., 2017), they were subsequently
referred to as “rasps.” Rasps were highly variable in dura-
tion, number of ticks, and frequency structure (Figs. 1and
2). Rasp frequency ranged from 344 to 33 968 Hz, with an
average peak frequency of 3409 Hz 6118 (Table I).
Additional frequency- and time-based measurements of
sablefish rasps are presented in Table I.
Mm. 2. Audio clip of long sablefish rasp (with more than
eight ticks) corresponding to the spectrogram displayed
in Fig. 2(A). This is a file of type “WAV” (843 KB).
Mm. 3. Audio clip of long sablefish rasp (with more than
eight ticks) corresponding to the spectrogram displayed
in Fig. 2(B). This is a file of type “WAV” (840 KB).
Mm. 4. Audio clip of long sablefish rasp (with more than
eight ticks) corresponding to the spectrogram displayed
in Fig. 2(C). This is a file of type “WAV” (1543 KB).
In addition to inter-rasp frequency variation, the inspec-
tion of individual ticks uncovered wide intra-rasp frequency
variation (Table II). Some rasps were made of ticks whose
bandwidth remained relatively constant throughout the entire
call (e.g., the tick with the greatest bandwidth was only about
400 Hz higher than the tick with the smallest bandwidth).
Other rasps presented bandwidth variability among their ticks
as great as 27.5 kHz. For some rasps, the bandwidth was
greater for the first few ticks, and then became narrower as the
call progressed [e.g., Figs. 1and 2(A)]. Most rasps exhibited
significant positive correlations between one or more tick fre-
quency measures and elapsed time within the rasp (see supple-
mentary Table I in the supplemental material
). Examples of
both significant positive and negative trends in tick frequency
The duration of ticks ranged between 1 and 53 ms, with
an average of 11 ms 60.1 (Table II). The period ranged
between 0.2 and 64.3 ms, with an average of 6 ms 60.1
(Table II). Within the same rasp, the period varied as little
as 0.2 ms (in a rasp with 3 ticks) and as much as 62.7 ms
(in a rasp with 23 ticks).
The analysis of the recordings collected at both loca-
tions revealed a total of 260 broadband high-frequency
sounds (average 3 KHz peak) referred to as rasps. These
sounds were composed of a series of short (average 11 ms),
broadband tick sounds that varied in frequency content and
time-interval between successive ticks (period). These char-
acteristics match the description of the sounds reported by
Meldrim (1965) from his unpublished study on captive
sablefish, and also support the hypothesis that sablefish
could have been the source of the broadband pulses recorded
by Sirovic et al. (2012) in Barkley Canyon. The attribution
of the rasp sounds to sablefish was supported by independent
observations in two different facilities. Real-time
TABLE I. Acoustic variables for sablefish (Anoplopoma fimbria) rasps recorded at two facilities, showing stats for each of them and both pooled together.
SE ¼standard error of the mean. Min ¼minimum. Max ¼maximum. F. ¼Frequency. BW ¼Bandwidth. F. 5% is the frequency that divides the signal into
two frequency intervals containing 5% and 95% of the energy in the signal. F. 95% is the frequency that divides the signal into two frequency intervals con-
taining 95% and 5% of the energy in the signal. BW 90% is the difference between the 5% and 95% frequencies.
Acoustic variables
GESF (N¼152) Manchester Research Station (N¼108) Pooled (N¼260)
Min Max Mean (6SE) Min Max Mean (6SE) Min Max Mean (6SE)
Low F. (Hz) 535 11 668 2446 6111 344 4817 1826 699 344 11 668 2188 679
F. 5% (Hz) 551 11 766 2552 6113 773 5859 23586109 551 11 766 2471 680
Peak F. (Hz) 574 12 258 3086 6144 434 9234 38636192 434 12 258 3409 6118
F. 95% (Hz) 1816 13 090 5418 6182 2203 30 305 94936581 1816 30 305 7111 6291
High F. (Hz) 2053 13154 6549 6209 2395 33 968 11 362 6716 2053 33 968 8548 6353
BW 90% (Hz) 375 8988 2866 6150 891 25 711 71366528 375 25 711 4640 6269
Duration (ms) 74 4323 732 652 98 10 493 22016192 74 10 493 1342 696
TABLE II. Acoustic variables for the sablefish (Anoplopoma fimbria) ticks
recorded at the Manchester Research Station (N¼2136 except for the
period and inter-tick interval where N¼2064, and the tick repetition rate
where N¼72). Ticks are the broadband pulses that make up the rasps.
These ticks were measured from a sub-sample of 72 rasps. SE ¼standard
error of the mean. Min ¼minimum. Max ¼maximum. F. ¼Frequency.
BW ¼Bandwidth. F. 5% is the frequency that divides the signal into two
frequency intervals containing 5% and 95% of the energy in the signal. F.
95% is the frequency that divides the signal into two frequency intervals
containing 95% and 5% of the energy in the signal. BW 90% is the differ-
ence between the 5% and 95% frequencies.
Acoustic variables Min Max Mean (6SE)
Low F. (Hz) 401 22 140 2570 639
F. 5% (Hz) 797 22 406 3178 639
Peak F. (Hz) 1066 23801 5398 662
F. 95% (Hz) 2133 32180 10 540 6102
High F. (Hz) 2481 41 463 12 225 6114
BW 90% (Hz) 363 28 852 7362 696
Duration (ms) 1 53 11 60.1
Number of ticks/rasp 3 336 30 65
Period (ms) 0.2 64.3 6 60.1
Inter-tick interval (ms) 0 63 5 60.1
Tick repetition rate (number of ticks/s) 5 63 18 61
J. Acoust. Soc. Am. 147 (4), April 2020 Riera et al. 2297
observations at GESF indicated that an artificial source of
the sounds was highly unlikely, though the possibility of
other biological sources could not be ruled out in the open
water pens. However, recordings of the same type of sounds
in tanks of adult sablefish at the NWFSC-MRS facility
confirmed sablefish as the only possible source. The fact
that rasps were recorded in multiple tanks with adults but
were absent from other tanks further reduces the likelihood
that they were artifacts.
This newly validated description of sablefish sounds
suggests that PAM surveys for sablefish can be used both in
fisheries applications and in studies of deep-sea ecology in
areas within the species’ geographic range.
Sablefish is one of the top 10 key commercial species in
the U.S., with an important fishery in the North Pacific Region
(Alaska) and Pacific Region (California, Oregon,
Washington), where the total annual landings revenue was
between 102 and 185 10
U.S. dollars between 2006 and
2015 (National Marine Fisheries Service, 2017). In British
Columbia, there have been concerns about the sablefish stock
declining below a sustainable yield, and management strate-
gies have been designed to promote stock growth while
FIG. 2. Three examples of sablefish rasps illustrating the high variation in rasp
structures and variation in tick frequency structure produced by sablefish
(Anoplopoma fimbria) at the Northwest Fisheries Science Center in Manchester.
Each example includes waveform (top) and spectrogram (bottom) (1800 FFT
Hann window with 85% overlap). A clip of each sound is available as multime-
dia files (Mm. 2–Mm. 4). (A) Rasp with a trend for increasing F.5. (Mm. 2).
The top panel is an expansion of the first tick in the middle panel, delineated
with a box. (B) Rasp with relatively constant tick frequency structure (Mm. 3).
(C) Long rasp with high variation in tick frequency structure (Mm. 4).
FIG. 3. (Color online) Examples of two rasps exhibiting significant correla-
tions of tick frequency parameters (5% frequency: square, peak frequency:
triangle, 95% frequency: circle) with the elapsed time from the beginning
of the rasp. The Spearman Rank Correlation (r) is indicated for 95% fre-
quency (top), peak frequency (middle), and 5% frequency (bottom) with
asterisks representing its significance level (* ¼0.05, ** ¼0.01,
*** ¼0.001, ns ¼not significant). (Top) Positive correlation (rasp ID 39 in
the supplementary table in the supplemental material
). (Bottom) Negative
correlation (rasp ID 48 in the supplementary table in the supplemental
2298 J. Acoust. Soc. Am. 147 (4), April 2020 Riera et al.
attempting to maintain the economic performance (Cox et al.,
2011). Stock biomass is currently assessed via trawling sur-
veys and fishery catch data (Wilkins and Saunders, 1997;
Koslow et al., 2000;Warpinski et al., 2016). The use of PAM
has the potential to enhance current sablefish management by
providing another independent monitoring tool.
The sablefish fishery in the Gulf of Alaska suffers great
reductions in catches due to sperm whale (Physeter macro-
cephalus) and killer whale (Orcinus orca) depredation on
longline fishing gear (Peterson and Hanselman, 2017;Wild
et al., 2017). An acoustic decoy has been used to broadcast
vessel-hauling noises known to attract whales at a distance
away from the vessel performing true hauls, thus reducing
the number of interactions between whales and fishing ves-
sels (Wild et al., 2017). It would be interesting to investigate
the response of whales to sablefish sounds. If whales are
attracted to rasps, perhaps adding recordings of sablefish
rasps to the vessel-hauling sounds could increase the effi-
cacy of the decoy as an attractant.
The soundscape of the deep-sea is poorly known, and
fish sounds have been described for very few deep-sea spe-
cies (see reviews in Rountree et al., 2012;Wall et al., 2014;
Parmentier et al., 2018). This limited knowledge could be
due to a series of factors including the need for specialized
equipment, inaccessibility, the non-continuous nature of fish
sound production (they might not be vocal at the moment of
recording), and the low amplitude of fish sounds that makes
them susceptible to masking and reduces their detection
range (Rountree et al., 2012;Wall et al., 2014). The results
presented here add sablefish as one of the few demonstrated
cases of sound production in deep-sea fishes. Knowing what
sablefish sound like will also facilitate a more complete
understanding of events that are already being monitored
with video at underwater cabled observatories (Doya et al.,
2014) where concurrent acoustic recordings are available.
This study demonstrates that sablefish produce sounds, and
therefore this knowledge is useful for PAM studies. How and
why the fish make the sound (if there is a specific function) is
unknown, and what follows is a discussion of some options.
The mechanism by which sablefish produce sounds is
currently unknown. The phylogenetic relationships of sable-
fish to other scorpaeniform fishes is uncertain, but the family
Anoplopomatidae is currently thought to be most closely
related to the greenlings (Hexagrammidae) and sculpins
(Cottidae) (Imamura and Yabe, 2002;Shinohara and
Imamura, 2007;Nelson et al., 2016). Unfortunately, despite
the high diversity of sculpins, sounds have only been
described in two genera (see reviews in Zeyl et al., 2016;
Bolgan et al., 2019) and it is unknown in greenlings.
The broadband high-frequency rasps produced by sable-
fish are highly unusual among fish, and previously unknown
for any scorpaeniform fish (Bolgan et al., 2019). High fre-
quency fish sounds have been reported for Clupeiformes
(Wilson et al., 2004;Rountree et al., 2018), Cypriniformes
and Salmoniformes (Rountree et al., 2018), Perciformes such
as grunts (Bertucci et al.,2014) and cichlids (Lanzing, 1974;
Nelissen, 1978;Kottege et al., 2015;Spinks et al., 2017),
Siluriformes (Ghahramani et al., 2014;Mohajer et al., 2015),
and Gadiformes (Vester et al., 2004). An important distinction
between the high frequency sounds produced by sablefish and
those produced by other fishes, is that in most other known
cases, the sound production mechanism involves the gas blad-
der (Tavolga, 1971;Ladich, 2004) which is absent in sablefish
(Nelson et al., 2016). In fish that lack a swim bladder, the most
common sound-producing mechanism is stridulation, which
consists of rubbing hard body parts together, such as bones,
teeth, or fin spines (Tavolga, 1971;Ladich, 2004). The high
variation in sablefish rasp frequency is consistent with a stridu-
latory mechanism (Fine and Parmentier, 2015). For the sculpin
species whose sound production has been described, average
peak frequency was between 50 and 500 Hz (Zeyl et al., 2016),
which is much lower than that of sablefish ticks (5398 662 Hz;
Table II). The tick duration for cottid fishes was also shorter
than that of sablefish; an average of 30 64ms to 68612 ms
(Zeyl et al., 2016)comparedto1160.1 ms (Table II).
High frequency stridulatory sounds can also be found in
some catfish (Ghahramani et al., 2014;Mohajer et al.,2015),
grunt (Bertucci et al., 2014), and cichlid (Lanzing, 1974;
Nelissen, 1978;Kottege et al.,2015;Spinks et al.,2017)spe-
cies. The average peak frequency for catfish has been reported
to be between 521 6240 Hz and 2895 6276 Hz (Parmentier
et al., 2010), while the average peak frequency for grunts was
718 6180 Hz (Bertucci et al.,2014). Sounds produced by
grunts also consisted of a series of units that were themselves
composed of a variable number of pulses (Bertucci et al.,2014).
In sablefish, frequency parameters vary greatly between ticks
within the same rasp (Fig. 3), but how the frequency of each
unit varies within the series is not described for grunts, making
comparisons difficult. One of the biggest differences between
sablefish rasps and the cichlid high-frequency sounds is the
number of components; cichlids have calls composed of an
average of two pulses (Spinks et al.,2017), whereas sablefish
difference translates into an overall longer duration for rasps.
Another less well-known sound production mechanism
found in some scorpaeniform species uses a novel
“chordophone” mechanism involving vibrations of tendons
to achieve higher frequencies than possible through muscle
contraction alone (see review in Bolgan et al., 2019). Future
research is needed to determine if sablefish sounds are pro-
duced by a stridulatory, chordophone, or other mechanism.
Although the lack of a swim bladder precludes an air
movement sound production mechanism (see review in
Rountree et al., 2018) in sablefish, a superficial similarity to
Pacific herring (Clupea pallasii) “fast repetitive tick” (FRT)
sounds has implications for PAM applications. Pacific herring
sounds are also composed of long trains of up to 65 ticks
(Wilson et al., 2004). The durations of rasps and FRTs are also
comparable, ranging between 0.7 and 10.5 s (average 1.3 s) for
rasps and 0.6 and 7.6 s (average 2.6 s) for FRTs (Wilson et al.,
2004). However, the period for rasps was highly variable (pre-
senting no clear pattern), whereas the period for herring FRTs
usually increases or decreases at a steady rate (Wahlberg and
Westerberg, 2003;Wilson et al., 2004;Kuznetsov, 2009).
J. Acoust. Soc. Am. 147 (4), April 2020 Riera et al. 2299
Most fishes where hearing has been examined hear best
around 200 Hz (Mann et al., 2007) and have audibility thresh-
olds up to 3 kHz (Ladich and Fay, 2013) but sablefish rasps
can get up to 30 kHz and whether they can hear their own
sounds remains unknown. The ability to produce sounds is not
necessarily associated with a matching sensitivity to hear
them (Ladich, 2000), so an inability to hear the rasps does not
preclude the possibility of other functions such as predator
avoidance. However, high frequency hearing exists for some
fishes in the subfamily Alosinae, which have been reported to
hear ultrasounds from 40 to 80 kHz (Mann et al.,2001).
Those Alosinae species can also hear the lower frequency
components of sounds, down to 200 Hz (Mann et al.,2001),
which indicates that the ability to hear ultrasounds does not
rule out the ability to hear low frequencies. All fishes can
detect particle motion through the otolith organs, but their
ability to perceive sound pressure could be limited to the pres-
ence of gas-filled structures (Hawkins and Popper, 2018),
which are absent in sablefish (Nelson et al.,2016). Sablefish
rasps have a mean peak of 3409 6118 Hz (Table I), which
falls within the range of hearing thresholds of hearing special-
ists (Ladich, 2000), so it is possible they have evolved a simi-
lar hearing specialist ability through an unknown mechanism
not involving the gas bladder. The hearing abilities of sable-
fish need to be investigated, and if possible, such studies
should design methodologies that produce data that are com-
parable between species and laboratories (Popper et al.,2019).
The skilfish, Erilepis zonifer, is the only other species
in the family Anoplopomatidae (Froese and Pauly, 2019). A
few studies have been conducted on the distribution and
biology of the skilfish (Zolotov et al., 2014), but no data is
available regarding their possible sound production. The
capacity for sound production is often shared by species of
the same family (Wall et al., 2014;Spinks et al., 2017;
Parmentier et al., 2018), which makes the skilfish a good
candidate for further studies to verify the hypothesis.
Although sound production in sablefish has been demon-
strated, it remains unclear if the sounds are produced for an
acoustic function such as intra-species communication which
requires an unexpected ability to hear high frequency sounds,
an inter-species signal that aids in predator avoidance which
does not require hearing sensitivity, or is entirely incidental to
some unknown physiological function. Regardless, the
description of sablefish sounds provides scientists with the
opportunity to use PAM methodologies in the study and man-
agement of the species. In addition, even if entirely incidental,
determination of the physiological mechanism that produces
such unusual sounds would be informative in and of itself,
and suggests that PAM could be used to monitor spatial and
temporal patterns in that physiological process. Future work
could include studies on hearing, sound production mecha-
nism, and behaviours associated with vocal activity.
The authors would like to thank Hannah Britton-Foster
and Kelsie Murchy for their assistance in the field. Thanks
are also due to the crew at the GESF (Terry Brooks,
Quinten, Dave, Trevor, Mike, Anthony) and personnel at the
Manchester Research Station (Rick Goetz and Cortney
Jensen). We are grateful to MERIDIAN for their support.
Funding was provided by DFO Contribution Agreements, an
NSERC Discovery grant, CFI and BCKDF equipment
grants, and the Liber Ero Foundation.
See supplementary material at for
details on the Spearman Rank Correlation of acoustic log transformed fre-
quency measures of ticks against time for rasps with eight or more ticks.
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... Seafloor multiparametric cabled observatories represent a wellestablished solution for the remote and continuous monitoring of the marine environment (Favali and Beranzoli, 2006;Ruhl et al., 2011;De Leo et al., 2018;Aguzzi et al., 2019;Dañobeitia et al., 2020;Rountree et al., 2020). These permanent seafloor infrastructures host complex and multidisciplinary sets of physical, chemical, and geological sensors designed to meet the challenges of integrated and large-scale oriented basic and applied science. ...
... In this context, ocean cabled observatories should also align their strategic planning with the Sustainable Development Goals set by the United Nations (European Multidisciplinary Seafloor and water column Observatory, 2020), which call for the monitoring of essential ecosystem services, which include healthy fish stocks and sustainable fisheries. Therefore, it becomes crucial to develop standardized monitoring programmes specifically dedicated to the production of real-time biological and environmental data assisting fishery-independent stock assessments (Aguzzi et al., 2015Rountree et al., 2020). ...
... The installation of video cameras on cabled instrument platforms is a breakthrough for marine ecology and associated monitoring programmes and policies (Bicknell et al., 2016;Aguzzi et al., 2019;Rountree et al., 2020). Biodiversity of megafauna can be assessed and quantified using time-lapse imaging at frequency intervals as short as minutes and for the duration of multiple year Cabled observatory fishery-independent stock assessment periods (Aguzzi et al., , 2015Lelièvre et al., 2017), when video data are adequately cross-referenced with physical samples for taxonomic determination (Howell et al., 2019). ...
Seafloor multiparametric fibre-optic-cabled video observatories are emerging tools for standardized monitoring programmes, dedicated to the production of real-time fishery-independent stock assessment data. Here, we propose that a network of cabled cameras can be set up and optimized to ensure representative long-term monitoring of target commercial species and their surrounding habitats. We highlight the importance of adding the spatial dimension to fixed-point-cabled monitoring networks, and the need for close integration with Artificial Intelligence pipelines, that are necessary for fast and reliable biological data processing. We then describe two pilot studies, exemplary of using video imagery and environmental monitoring to derive robust data as a foundation for future ecosystem-based fish-stock and biodiversity management. The first example is from the NE Pacific Ocean where the deep-water sablefish (Anoplopoma fimbria) has been monitored since 2010 by the NEPTUNE cabled observatory operated by Ocean Networks Canada. The second example is from the NE Atlantic Ocean where the Norway lobster (Nephrops norvegicus) is being monitored using the SmartBay observatory developed for the European Multidisciplinary Seafloor and water column Observatories. Drawing from these two examples, we provide insights into the technological challenges and future steps required to develop full-scale fishery-independent stock assessments.
... Sperm whales (Physeter microcephalus) follow longline fishing vessels and the NMFS longline survey vessels in the GOA and use echolocation at frequencies from 100 Hz to 30 kHz [26,27] to depredate fishing gear, when locating fish after they are removed from the hook (and before they can return to the benthos), and likely when identifying prey under natural conditions [5,[28][29][30]. Sablefish create vibrations from 344 Hz to 34 kHz [31], which are very similar to sperm whales. Although there is no evidence of SST creating vibrations, the sablefish results demonstrate that a species without a swim bladder may be able to create and detect cetacean acoustics at these frequencies. ...
... For example, SST are sedentary and are often resting on the bottom, either in depressions or in associations with bottom structure [3]. The reflexes needed by SST may be dissimilar to fish with different life histories, such as those living in the pelagic zone or schooling, or for species that are known to make vibration, possibly for communication, like deepwater sablefish [31]. It is unknown how a lack of these reflexes will affect a sedentary species if they are permanent. ...
Full-text available
Shortspine thornyhead (Sebastolobus alaskanus) are a benthic, deepwater species in the family Scorpaenidae. They have been tagged annually in Alaska since 1992, but have a low tag return rate of 1.6%. This may be at least partially attributed to post-release mortality related to capture. In this study, 21 shortspine thornyhead were caught on bottom hook-and-line longline gear and immediately given reflex tests. Eighteen were transported to the laboratory and held for 10-42 days, given reflex tests again, and then given postmortem examinations, including histopathology of tissues; three were given postmortem examinations after reflex tests on the vessel. There were no histological findings that could be directly linked to capture and holding; however, there were occurrences of myxozoan (protozoa) and metazoan (nematode) parasites, sometimes associated with minor inflammation. The vibration response reflex was found in only 24% of fish on deck and in 56% of fish after holding in the laboratory. The vestibular-ocular response was present in 47% of fish on deck and 89% of fish in the laboratory. A fish's ability to right itself was successful on deck in 43% of fish (an additional 19% responded slowly) and 100% in the laboratory. Some reflex impairments may be permanent or may take more than days or weeks to improve. Reflex responses to other tests, the tail grab, gag, and operculum flare, were 95-100% successful on deck and later in the laboratory. A lack of reflexes may increase the risk of predation after release and may affect other behaviors related to survival and productivity.
... in the other climate zones, and all climate zones had similar percentages of actively soniferous species out of the number of species examined ( Table 2). Because of the low visibility of the polar regions during the winter, fish sound production may be even more likely, but research about fishes and their sound production in polar regions has been slowed by technical limitations, expense, and low encounter rates of study species (Klinck et al. 2016;Riera et al. 2020). We, therefore, anticipate that with further research, actively soniferous fish species will be observed in the Antarctic regions. ...
... This situational specificity makes declaring a species conclusively nonactively soniferous challenging, which is further complicated by positive publication bias, leading to underreporting of negative results (Mlinarić et al. 2017). Some groups, such as deep-sea fishes, may be particularly difficult to study auditorily due to inaccessibility (Marshall 1967;Rountree et al. 2012;Riera et al. 2020;. In fact, 81.9% of the deep-water species included in the review were only examined morphophysiologically. ...
Full-text available
Sound production in fishes is vital to an array of behaviors including territorial defense, reproduction, and competitive feeding. Unfortunately, recent passive acoustic monitoring efforts are revealing the extent to which anthropogenic forces are altering aquatic soundscapes. Despite the importance of fish sounds, extensive endeavors to document them, and the anthropogenic threats they face, the field of fish bioacoustics has been historically constrained by the lack of an easily accessible and comprehensive inventory of known soniferous fishes, as is available for other taxa. To create such an inventory while simultaneously assessing the geographic and taxonomic prevalence of soniferous fish diversity, we extracted information from 834 references from the years 1874–2020 to determine that 989 fish species from 133 families and 33 orders have been shown to produce active (i.e., intentional) sounds. Active fish sound production is geographically and taxonomically widespread—though not homogenous—among fishes, contributing a cacophony of biological sounds to the prevailing soundscape globally. Our inventory supports previous findings on the prevalence of actively soniferous fishes, while allowing novel species-level assessments of their distribution among regions and taxa. Furthermore, we evaluate commercial and management applications with passive acoustic monitoring, highlight the underrepresentation of research on passive (i.e., incidental) fish sounds in the literature, and quantify the limitations of current methodologies employed to examine fishes for sound production. Collectively, our review expands on previous studies while providing the foundation needed to examine the 96% of fish species that still lack published examinations of sound production.
... The sound response may be important for locating prey or for evading predators, as sablefish are one of the few deep-sea fish that have been shown to make sound and, therefore, may hear sound [25]. Sperm whales (Physeter microcephalus) follow hook-andline longline fishing vessels in the Gulf of Alaska and depredate on the gear while hauling [26,27]. ...
... Sablefish acoustics range from 344 Hz to 34 kHz [24], which are very similar to sperm whales (100 Hz-30 kHz) [30,31]. Although sablefish have the ability to make sound, it is unknown if they detect sound or what frequencies they can detect, and what the hearing mechanism may be because they lack a swim bladder [25]. Despite these unknowns, it is possible that sablefish can hear some sperm whale sounds. ...
Full-text available
It is unknown if capture coupled with time out of water on-deck affect sablefish (Anoplopoma fimbria) health and reflexes, and whether it contributes to acute or delayed mortality. In this study, 35 sablefish were caught using hook-and-line gear and given six reflex tests after capture. Thirty-two were subsequently transported to the laboratory, held for 45–52 days, and then experimentally held out of the water for either 0, 3, 6, or 11 min. After 7–10 days of holding in the laboratory after the experiment, to monitor for mortalities, reflexes were tested for a second time and necropsies and histopathology were performed. There were no histological findings and no mortalities; however, parasites and minor inflammation were observed. All occurrences were not a result of capture or experiments. Some reflexes were absent after capture (77% could right themselves, 69% responded to a tail grab, and 57% responded to sound.) The only test where the reflex did not improve to 100% in the laboratory was the sound reflex. The sound reflex was highest for control fish (63%) and there were no positive sound reflexes for fish held out of water for 11 min. The absence of reflexes may result in predation after release and present issues with feeding or communication.
... The most common way to identify species and behaviourspecific sounds is to capture and isolate a single fish or several fish of the same species in a controlled environment (typically a fish tank) and record the sounds they produce (e.g. Riera et al., 2018Riera et al., , 2020. Such an experimental setup precludes sound contamination from other species and allows visual observation of the behaviour of the animal. ...
Full-text available
Associating fish sounds to specific species and behaviours is important for making passive acoustics a viable tool for monitoring fish. While recording fish sounds in tanks can sometimes be performed, many fish do not produce sounds in captivity. Consequently, there is a need to identify fish sounds in situ and characterise these sounds under a wide variety of behaviours and habitats. We designed three portable audio-video platforms capable of identifying species-specific fish sounds in the wild: a large array, a mini array and a mobile array. The large and mini arrays are static autonomous platforms than can be deployed on the seafloor and record audio and video for one to two weeks. They use multichannel acoustic recorders and low-cost video cameras mounted on PVC frames. The mobile array also uses a multichannel acoustic recorder, but mounted on a remotely operated vehicle with built-in video, which allows remote control and real-time positioning in response to observed fish presence. For all arrays, fish sounds were localised in three dimensions and matched to the fish positions in the video data. We deployed these three platforms at four locations off British Columbia, Canada. The large array provided the best localisation accuracy and, with its larger footprint, was well suited to habitats with a flat seafloor. The mini and mobile arrays had lower localisation accuracy but were easier to deploy, and well suited to rough/uneven seafloors. Using these arrays, we identified, for the first time, sounds from quillback rockfish Sebastes maliger, copper rockfish Sebastes caurinus and lingcod Ophiodon elongatus. In addition to measuring temporal and spectral characteristics of sounds for each species, we estimated mean source levels for lingcod and quillback rockfish sounds (115.4 and 113.5 dB re 1 μPa, respectively) and maximum detection ranges at two sites (between 10.5 and 33 m). All proposed array designs successfully identified fish sounds in the wild and were adapted to various budget, logistical and habitat constraints. We include here building instructions and processing scripts to help users replicate this methodology, identify more fish sounds around the world and make passive acoustics a more viable way to monitor fish.
... Sablefish (Anoplopoma fimbria) is a demersal fish species of the Pacific coast of North America (depth range 300-3000 m; Orlov, 2003), which supports important commercial fisheries (Warpinski et al., 2016;Riera et al., 2020). Sablefish populations include resident and migrating individuals performing both horizontal and vertical movements (Jacobson et al., 2001;Maloney and Sigler, 2008;Morita et al., 2012;Hanselman et al., 2015;Goetz et al., 2018;Sigler and Echave, 2019) across large geographic ranges (Chapman et al., 2012). ...
Full-text available
Ocean observatories collect large volumes of video data, with some data archives now spanning well over a few decades, and bringing the challenges of analytical capacity beyond conventional processing tools. The analysis of such vast and complex datasets can only be achieved with appropriate machine learning and Artificial Intelligence (AI) tools. The implementation of AI monitoring programs for animal tracking and classification becomes necessary in the particular case of deep-sea cabled observatories, as those operated by Ocean Networks Canada (ONC), where Petabytes of data are now collected each and every year since their installation. Here, we present a machine-learning and computer vision automated pipeline to detect and count sablefish ( Anoplopoma fimbria ), a key commercially exploited species in the N-NE Pacific. We used 651 hours of video footage obtained from three long-term monitoring sites in the NEPTUNE cabled observatory, in Barkley Canyon, on the nearby slope, and at depths ranging from 420 to 985 m. Our proposed AI sablefish detection and classification pipeline was tested and validated for an initial 4.5 month period (Sep 18 2019-Jan 2 2020), and was a first step towards validation for future processing of the now decade-long video archives from Barkley Canyon. For the validation period, we trained a YOLO neural network on 2917 manually annotated frames containing sablefish images to obtain an automatic detector with a 92% Average Precision (AP) on 730 test images, and a 5-fold cross-validation AP of 93% (± 3.7%). We then ran the detector on all video material (i.e., 651 hours from a 4.5 month period), to automatically detect and annotate sablefish. We finally applied a tracking algorithm on detection results, to approximate counts of individual fishes moving on scene and obtain a time series of proxy sablefish abundance. Those proxy abundance estimates are among the first to be made using such a large volume of video data from deep-sea settings. We discuss our AI results for application on a decade-long video monitoring program, and particularly with potential for complementing fisheries management practices of a commercially important species.
... The most common way to identify species and behaviourspecific sounds is to capture and isolate a single fish or several fish of the same species in a controlled environment (typically a fish tank) and record the sounds they produce (e.g. Riera et al., 2018Riera et al., , 2020. Such an experimental setup precludes sound contamination from other species and allows visual observation of the behaviour of the animal. ...
No PDF available ABSTRACT We describe three portable volumetric audio/video arrays capable of identifying species-specific fish sounds in the wild. Each array can record fish sounds, acoustically localize the fish in three-dimensions (using linearized or fully non-linear inversion), and record video to identify the species and observe their behavior. The design of each array accommodates specific logistical and financial constraints, covering a range of nearshore habitats and applications. The first platform is composed of six hydrophones, an acoustic recorder, and two video cameras secured to a 2 × 2 × 3 m PVC frame. Hydrophone placement is defined using simulated annealing to maximize localization accuracy. The second platform uses a single video camera, four hydrophones, and an acoustic recorder on a one cubic meter PVC frame. It can be deployed on heterogeneous substrates but has lower localization capabilities. The third platform consists of four hydrophones connected to an acoustic recorder mounted on a tethered underwater drone with built-in video. It allows remote control and real-time positioning in response to observed fish presence but with reduced localization capabilities. The three platforms were deployed off British Columbia, Canada, and used to identify and characterize new sounds from quillback rockfish, copper rockfish, and lingcod.
... Such limitations can be overcome by improving data acquisition technologies but also by adopting a multidisciplinary approach. In the context of monitoring fish communities, video data can be complemented not only with traditional survey methods but also with other non-invasive techniques such as simple passive acoustic monitoring of fish vocalizations (Pijanowski et al., 2011;Riera et al., 2020;Rountree, 2008;Rountree and Able, 2007;Staaterman et al., 2017) and eDNA (Taberlet et al., 2012), allowing species spatiotemporal traceability beyond that of optoacoustic assets capability (Aguzzi et al., 2019). eDNA studies target genetic material that is released from a source organism into its surrounding environment; this technology can be highly sensitive and, once established, is capable of taxonomic resolution to the species level without relying on specialized taxonomic expertise (Goldberg et al., 2016). ...
Cabled observatories are marine infrastructures equipped with biogeochemical and oceanographic sensors as well as High-Definition video and audio equipment, hence providing unprecedented opportunities to study marine biotic and abiotic components. Additionally, non-invasive monitoring approaches such as environmental DNA (eDNA) metabarcoding have further enhanced the ability to characterize marine life. Although the use of non-invasive tools beholds great potential for the sustainable monitoring of biodiversity and declining natural resources, such techniques are rarely used in parallel and understanding their limitations is challenging. Thus, this study combined Underwater Video (UV) with eDNA metabarcoding data to produce marine fish community profiles over a 2 months period in situ at a cabled observatory in the northeast Atlantic (SmartBay Ireland). By combining both approaches, an increased number of fish could be identified to the species level (total of 22 species), including ecologically and economically important species such as Atlantic cod, whiting, mackerel and monkfish. The eDNA approach alone successfully identified a higher number of species (59%) compared to the UV approach (18%), whereby 23% of species were detected by both methods. The parallel implementation of point collection eDNA and time series UV data not only confirmed expectations of the corroborative effect of using multiple disciplines in fish community composition, but also enabled the assessment of limitations intrinsic to each technique including the identification of false-negative detections in one sampling technology relative to the other. This work showcased the usefulness of cabled observatories as key platforms for in situ empirical assessment of both challenges and prospects of novel technologies in aid to future monitoring of marine life.
The American silver perch (Bairdiella chrysoura) is a numerically dominant and ecologically important species found throughout coastal habitats along the eastern United States and Gulf of Mexico. During spawning in the spring and summer, male silver perch produce distinctive knocking sounds to attract females. These sounds are readily identifiable through aural and visual analysis of underwater acoustic recordings, providing a means to track the distribution and spawning activity of these fish. However, as the volume of passive acoustic datasets grows, there is an essential need to automate the process of cataloguing silver perch vocalisations. The approach presented here utilises a (1) detection stage, where candidate calls are identified based on the properties of signal kurtosis and signal-to-noise ratio, (2) a feature extraction stage where layer activations are returned from the pre-trained ResNet-50 convolutional neural network operating on a wavelet scalogram of these signals, and (3) a one-vs-all support-vector-machine classifier. The labelled data used to build the classifier consists of 6000 perch calls and 6000 other signals that sample diverse acoustic conditions within the Pamlico Sound estuary, USA. The model accuracy is 98.9%, and the accompanying software provides an efficient tool to investigate silver perch calling patterns within passive acoustic data.
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Acoustic signaling by fishes has been recognized for millennia, but is typically regarded as comparatively rare within ray-finned fishes; as such, it has yet to be integrated into broader concepts of vertebrate evolution. We map the most comprehensive data set of volitional sound production of ray-finned fishes (Actinopterygii) yet assembled onto a family level phylogeny of the group, a clade representing more than half of extant vertebrate species. Our choice of family-level rather than species-level analysis allows broad investigation of sonifery within actinopterygians and provides a conservative estimate of the distribution and ancestry of a character that is likely far more widespread than currently known. The results show that families with members exhibiting soniferous behavior contain nearly two-thirds of actinopterygian species, with potentially more than 20,000 species using acoustic communication. Sonic fish families also contain more extant species than those without sounds. Evolutionary analysis shows that sound production is an ancient behavior because it is present in a clade that originating circa 340 Ma, much earlier than any evidence for sound production within tetrapods. Ancestral state reconstruction indicates that sound production is not ancestral for actinopterygians; instead, it independently evolved at least 27 times, compared to six within tetrapods. This likely represents an underestimate for actinopterygians that will change as sonifery is recognized in ever more species of actinopterygians. Several important ecological factors are significantly correlated with sonifery – including physical attributes of the environment, predation by members of other vertebrate clades, and reproductive tactics – further demonstrating the broader importance of sound production in the life history evolution of fishes. These findings offer a new perspective on the role of sound production and acousticcommunication during the evolution of Actinopterygii, a clade containing more than 34,000 species of extant vertebrates.
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The /Kwa/ vocalization dominates the soundscape of Posidonia oceanica meadows but the identity of the species emitting this peculiar fish sound remains a mystery. Information from sounds recorded in the wild indicates that the emitting candidates should be abundant, nocturnal and benthic. Scorpaena spp. combine all these characteristics. This study used an interdisciplinary approach to investigate the vocal abilities of Scorpaena spp.; morphological, histological and electrophysiological examinations were interpreted together with visual and acoustic recordings conducted in seminatural conditions. All observed Scorpaena spp. (S. porcus, S. scrofa and S. notata) share the same sonic apparatus at the level of the abdominal region. This apparatus, present in both males and females, consists of 3 bilaterally symmetrical muscular bundles, having 3–5 long tendons, which insert on ventral bony apophyses of the vertebral bodies. In all chordophones (stringed instruments), the frequency of the vibration is dependent on the string properties and not on the rate at which the strings are plucked. Similarly, we suggest that each of the 3–5 tendons found in the sonic mechanism of Scorpaena spp. acts as a frequency multiplier of the muscular bundle contractions, where the resonant properties of the tendons determine the peak frequency of the /Kwa/, its frequency spectra and pseudoharmonic profile. The variability in the length and number of tendons found between and within species could explain the high variability of /Kwa/ acoustic features recorded in the wild. Finally, acoustic and behavioural experiments confirmed that Scorpaena spp. can emit the /Kwa/ sound.
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We sought to describe sounds of some of the common fishes suspected of producing unidentified air movement sounds in soundscape surveys of freshwater habitats in the New England region of North America. Soniferous behavior of target fishes was monitored in real time in the field in both natural and semi-natural environments by coupling Passive Acoustic Monitoring (PAM) with direct visual observation from shore and underwater video recording. Sounds produced by five species including, alewife (Alosa pseudoharengus, Clupeidae), white sucker (Catastomus commersonii, Catostomidae), brook trout (Salvelinus fontinalis, Salmonidae), brown trout (Salmo trutta, Salmonidae), and rainbow trout (Oncorhynchus mykiss, Salmonidae) were validated and described in detail for the first time. In addition, field recordings of sounds produced by an unidentified salmonid were provisionally attributed to Atlantic salmon (Salmo salar, Salmonidae). Sounds produced by all species are of the air movement type and appear to be species specific. Our data based on fishes in three distinct orders suggest the phenomenon may be more ecologically important than previously thought. Even if entirely incidental, air movement sounds appear to be uniquely identifiable to species and, hence, hold promise for PAM applications in freshwater and marine habitats.
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Soundscape ecology is a rapidly growing field with approximately 93% of all scientific articles on this topic having been published since 2010 (total about 610 publications since 1985). Current acoustic technology is also advancing rapidly, enabling new devices with voluminous data storage and automatic signal detection to define sounds. Future uses of passive acoustic monitoring (PAM) include biodiversity assessments, monitoring habitat health, and locating spawning fishes. This paper provides a review of ambient sound and soundscape ecology, fish acoustic monitoring, current recording and sampling methods used in long-term PAM, and parameters/metrics used in acoustic data analysis.
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Sounds produced by Arctic cod were recorded for the first time and suggest passive acoustic monitoring (PAM) can be an effective additional tool for the study and management of the species. Each of the 38 calls detected in three different aquatic facilities consisted of a single grunt with 6 to 12 pulses and a mean duration of 289 ms. Call frequency ranged between 59 and 234 Hz, with a mean peak frequency of 107 Hz. These preliminary data suggest Arctic cod can be distinguished from other gadids, but additional studies of sympatric species are needed before PAM can be confidently adopted.
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Structured biogenic habitats are biodiversity hotspots that host a wide range of soniferous species. Yet in deep-water systems, their soundscapes are largely undescribed. In September of 2016 we deployed 3 underwater acoustic recorders for approximately 4 d in and around a glass sponge reef in the Outer Gulf Islands sponge reef fishing closure, British Columbia, Canada. The 2 recordings from the reef (within and at the margin of the reef footprint) were significantly louder in the mid- and high-frequency bands (100 to 1000 Hz and 1 to 10 kHz, respectively) than the recordings made in soft-bottom habitat away from the reef. These frequency bands are known to correlate with aspects of the biological community as well as benthic cover in shallow-water systems; visual surveys conducted in the area confirmed the presence of several known soniferous species. More fish sounds were recorded on the reef compared to the off-reef site. Our results suggest that this glass sponge reef has a distinct soundscape and that future work linking aspects of the soundscape to the ecology of the ecosystem are warranted. © W.D.H., A.R., X.M., M.K.P., F.J. and Fisheries and Oceans Canada 2018.
Directional hearing may enable fishes to seek out prey, avoid predators, find mates, and detect important spatial cues. Early sound localization experiments gave negative results, and it was thought unlikely that fishes utilized the same direction-finding mechanisms as terrestrial vertebrates. However, fishes swim towards underwater sound sources, and some can discriminate between sounds from different directions and distances. The otolith organs of the inner ear detect the particle motion components of sound, acting as vector detectors through the presence of sensory hair cells with differing orientation. However, many questions remain on inner ear functioning. There are problems in understanding the actual mechanisms involved in determining sound direction and distance. Moreover, very little is still known about the ability of fishes to locate sound sources in three-dimensional space. Do fishes swim directly towards a source, or instead “sample” sound levels while moving towards the source? To what extent do fishes utilize other senses and especially vision in locating the source? Further behavioral studies of free-swimming fishes are required to provide better understanding of how fishes might actually locate sound sources. In addition, more experiments are required on the auditory mechanism that fishes may utilize.
The ecological importance of the freshwater soundscape is just beginning to be recognized by society. Scientists are beginning to apply Passive Acoustic Monitoring (PAM) methods that are well established in marine systems to freshwater systems to map spatial and temporal patterns of behaviors associated with fish sounds as well as noise impacts on them. Unfortunately, these efforts are greatly hampered by a critical lack of data on the sources of sounds that make up the soundscape of freshwater habitats. A review of the literature finds that only 87 species have been reported to produce sounds in North America and Europe over the last 200 years, accounting for 5% of the known freshwater fish diversity. The problem is exacerbated by the general failure of researchers to report the detailed statistical descriptions of fish sound characteristics that are necessary to develop PAM programs. We suggest that publishers and editors should do more to encourage reporting of statistical properties of fish sounds. In addition, we call for research, academic, and government agencies to develop regional libraries of fish sounds to aid in PAM and anthropogenic noise impact studies. This article is protected by copyright. All rights reserved.
Cusk-eels (Ophidiidae) are known sound producers, but many species live in deep water where sounds are difficult to record. For these species sonic ability has been inferred from inner anatomy. Genypterus (subfamily Ophidiinae) are demersal fishes inhabiting the continental shelf and slope at depths between 50 and 800 m. Males and females G. maculatus have been maintained together in a tank and 9 unsexed specimens of G. chilensis in a second tank, providing a valuable opportunity to record the sounds of living species usually found at great depths. Genypterus chilensis and G. maculatus respectively produced one and two sound types mainly between 7 and 10 pm. Sound 1 in Genypterus maculatus consists of trains of pulses that vary in amplitude and pulse period; call 2 sounded like a growl that results from the rapid emission of pulses that define sound 1. Genypterus chilensis produced a growl having an unusual feature since the first peak of the second pulse has always greater amplitude than all other peaks. These sounds are probably related to courtship behavior since floating eggs are found after night calls. The anatomical structures of the sound-producing organ in both species present an important panel of highly derived characters including three pairs of sonic muscles, a neural arch that pivots on the first vertebral body and a thick swimbladder with unusual features. Sonic structures are similar between species and between sexes. Therefore both biological sexes are capable of sound production although precedent from shallow ophidiids and sonic fishes in general suggests that males are more likely to produce courtship calls. This study reports two main types of information. It demonstrates that two deep-living species are capable of sound production, which is a pioneer step in the acoustic study of deep-sea fauna. Recorded sounds should also help to locate fish in open sea. As these species are currently used to diversify the aquaculture industry in Chile, deeper studies on their acoustic behavior should also help to target spawning period and to identify mature specimens.
In the Gulf of Alaska, sperm whales (Physeter macrocephalus) are known to remove sablefish (Anoplopoma fimbria) from commercial longline fishing gear. This removal, called depredation, is economically costly to fishermen, presents risk of injury or mortality to whales, and could lead to unknown removals during the federal sablefish longline survey that contributes to estimation of the annual fishing quota. In 2013 the Southeast Alaska Sperm Whale Avoidance Project (SEASWAP) evaluated the efficacy of an acoustic decoy in reducing encounters between sperm whales and longline fishing gear. The aim of the acoustic decoy was to use fishing vessel sounds to attract whales to an area away from the true fishing haul in order to reduce interactions between commercial fishing vessels and whales. A custom playback device that could be remotely activated via a radio modem was incorporated into an anchored buoy system that could be deployed by the vessel during a two-month trip between June and July 2013. Once activated, the decoy broadcasted vessel-hauling noises known to attract whales, while the vessel performed several true hauls at various ranges from the device. Passive acoustic recorders at both the decoy and true set locations were also deployed to evaluate whale presence. Twenty-six hauls were conducted while a decoy was deployed, yielding fourteen sets with whales present while the decoy was functional. A significant relationship was found between the number of whales present at the true fishing haul and the distance of the haul from the decoy (1–14 km range), with the decoy being most effective at ranges greater than 9 km (t = −2.06, df = 12, p = 0.04). The results suggest that acoustic decoys may be a cost-effective means for reducing longlining depredation from sperm and possibly killer whales under certain circumstances.